About the Role
LeadSquared is looking for a Senior AI/ML Engineer who brings a strong combination of traditional Machine Learning expertise and hands-on experience building Agentic AI systems.
The ideal candidate will be responsible for designing, developing, and deploying intelligent AI/ML solutions that power LeadSquared's products, while also building the next generation of LLM-powered agents, AI workflows, and autonomous decision-making systems.
This role requires someone who can go beyond experimentation and take AI solutions from problem definition → model development → production deployment → monitoring and continuous improvement.
Key Responsibilities
- Design, develop and deploy ML models for real-world business and product use cases.
- Work on LLMs, Generative AI and Agentic AI applications.
- Build AI agents capable of reasoning, planning, tool calling and multi-step task execution.
- Develop RAG pipelines, embeddings, vector search and knowledge-based AI systems.
- Design agent workflows involving function/tool calling, memory, context management and orchestration.
- Build and evaluate multi-agent systems where applicable.
- Apply traditional ML techniques including classification, regression, ranking, recommendation, NLP and predictive modelling.
- Fine-tune and optimize LLMs/models for specific business use cases.
- Develop robust evaluation frameworks for LLM and agent performance, accuracy, hallucination, latency and cost.
- Productionize AI/ML models and integrate them with scalable product architectures.
- Work closely with Product, Engineering, Data Science and Business teams to identify and solve high-impact problems.
- Optimize AI systems for performance, scalability, reliability and cost efficiency.
- Establish best practices around MLOps, model monitoring, experimentation and continuous improvement.
Must-Have Skills
- Strong programming experience in Python.
- Strong fundamentals in Machine Learning, Deep Learning, NLP and Statistics.
- Hands-on experience with LLMs and Generative AI.
- Strong understanding of RAG, embeddings, vector databases and semantic search.
- Experience with Agentic AI / AI Agents, including tool calling and workflow orchestration.
- Experience with frameworks such as LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI or equivalent.
- Experience working with models/APIs such as OpenAI, Anthropic, Gemini, Llama or equivalent.
- Experience with PyTorch/TensorFlow and ML libraries such as Scikit-learn.
- Good understanding of REST APIs, microservices and cloud platforms.
- Experience taking AI/ML solutions into production environments.
Good to Have
- Experience building multi-agent architectures.
- Experience with AI evaluation, observability and guardrails.
- Experience with fine-tuning, LoRA/PEFT or model optimization.
- Knowledge of MLOps/LLMOps.
- Experience with AWS/Azure/GCP.
- Experience with Kafka, Redis, Docker/Kubernetes or similar technologies.
- Experience in SaaS, CRM, MarTech, SalesTech or enterprise applications.
What We Are Looking For
We are looking for a builder, not someone who has worked only on AI POCs or research projects. The candidate should demonstrate the ability to combine strong ML fundamentals with modern Agentic AI capabilities and build reliable, production-grade AI solutions.
Ideal profile:
Traditional ML + GenAI/LLM + Agentic AI + Production Engineering + Strong Product Mindset.
Shubham Vishwakarma
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Click the link below to fill the application form:
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Follow CutshortShubham Vishwakarma
Full Stack Developer - Averlon